In recent years, Learning Analytics (LA) has become a very heterogeneous research field due to the diversity in the data generated by the Learning Management Systems (LMS) as well as the researchers in a variety of disciplines, who analyze this data from a range of perspectives. In this paper, we present the evaluation of a LA tool that helps course designers, teachers, students and educational researchers to make informed decisions about the selection of learning activities and LA indicators for their course design or LA dashboard. The aim of this paper is to present Open Learning Analytics Indicator Repository (OpenLAIR) and provide a first evaluation with key stakeholders (N=41). Moreover, it presents the results of the prevalence of indicators that have been used over the past ten years in LA. Our results show that OpenLAIR can support course designers in designing LA-based learning activities and courses. Furthermore, we found a significant difference between the relevance and usage of LA indicators between educators and learners. The top rated LA indicators by researchers and educators were not perceived as equally important from students' perspectives.

Learning analytics are utilized to support learners’ educational needs as well as to enhance their study success, for example, via the use of real-time prompts, motivational dashboards, and appropriate learning interventions, which have been shown to increase students’ academic performance as well as their course retention rates. Yet, the perspective of higher education teachers in utilizing analytics to help analyze, reflect on, and improve their teaching design prior to delivery as well as to monitor and measure how the students engaged with their learning processes has been less recognized. In this paper, we present the results of a systematic review conducted from higher education teachers’ perspective concerning how analytics can be deployed to adapt the curriculum to suit better students’ educational needs in order to increase their study success. Thirty-five key studies were identified showing that analytics have been successful in influencing positively study success via teachers’ academic curriculum intervention. Specifically, via analytics, higher education teachers could rapidly visualize common course pathways and identify any difficulties students experienced in real-time in order to increase their learning experiences and outcomes.

We currently utilize the Moodle learning management system for teachers and students who participate in the course ‘College of Liberal Arts and Sciences’ at Kobe University in Japan. Digital textbooks, reports, quizzes and questionnaires in this course were administered using Moodle. In this paper, we proposed to use quizzes to measure and evaluate those digital textbooks recorded on Moodle. At the beginning of our study, we examined the questions that students got lower scores, and then we found the related teaching materials of digital textbooks and feedback to the teachers in order to improve the content of these digital textbooks.

It is necessary to perform a literature review before starting a new research project. However, many students do not know the procedures of performing a literature review. In this paper, based on the professional experiences and opinions of expert researchers, we describe an SNS-based literature review system to help students conduct research surveys. This system includes two search engines, one is an article search engine, which can help students conduct research surveys, and the other is a logging search engine, which allows students to learn from each other via their logs and share experience with other students. User models of the system as well as its functions are presented.

We develop an innovative mathematical mobile learning activity for 12 year old students, who are asked to coordinate themselves physically in terms of given distances with respect to two given points in an outdoor setting. The development of the outdoor activity poses pedagogical as well as technological design challenges. In this paper, we elaborate on two critical incidents that occurred during the implementation of the activity. Such incidents call for increasing attention to the negotiation of pedagogical and technological requirements during the design process. We argue that the efficient development of innovative mobile learning activities aiming at supporting learning in outdoors and indoors settings requires effective negotiation and coordination of pedagogical and technological strategies and requirements during the entire design process.

In recent years, mobile and context-aware technologies have been used in an attempt to enhance students‟ formal and informal learning experiences both in the classroom and outdoor settings. Such technologies have supported teaching and learning in a variety of subjects. In this paper, we present the ongoing research efforts in our Geometry Mobile (GeM) project, where we conducted a number of trials in the last two years with primary and secondary school students in Sweden. The current trial of our GeM project (April 2011) is discussed together with the data collection method we have used for exploring how Context-Aware learning hints (CA hints) can be utilized to support the different stages of the learning activity. Insights and preliminary results from this trial are described. We also present the motivation of our proposed CA hints, the definition of the requirements of those, and the formulation of a classification thereof.

Novice programmers require large amounts of time and motivation to learn an object-oriented programming language such as Java. In this paper, the architecture of our context-aware and adaptive learning schedule (CALS) tool is described. The tool has been designed to focus initially on supporting first year computer science undergraduate students to become more proficient Java programmers, and makes use of a learning schedule, where the learner inputs their daily activities. Based on this information, the tool is able to automatically determine the contextual features such as the location and available time. The appropriate learning materials are selected for the students according to, firstly, the learner preferences (such as learning styles), and secondly the contextual features (such as the level of concentration).